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Achieving Perfect Location Privacy in Wireless Devices Using Anonymization

机译:使用匿名化在无线设备中实现完美的位置隐私

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The popularity of mobile devices and location-based services (LBSs) has raised significant concerns regarding the location privacy of their users. A popular approach to protect location privacy is anonymizing the users of LBS systems. In this paper, we introduce an information-theoretic notion for location privacy, which we call perfect location privacy. We then demonstrate how anonymization should be used by LBS systems to achieve the defined perfect location privacy. We study perfect location privacy under two models for user movements. First, we assume that a user's current location is independent from her past locations. Using this independent identically distributed (i.i.d.) model, we show that if the pseudonym of the user is changed before O(n2/r-1 ) observations are made by the adversary for that user, then the user has perfect location privacy. Here, n is the number of the users in the network and r is the number of all possible locations. Next, we model users' movements using Markov chains to better model real-world movement patterns. We show that perfect location privacy is achievable for a user if the user's pseudonym is changed before O(n 2/IEI-r observations are collected by the adversary for that user, where IEI is the number of edges in the user's Markov chain model.
机译:移动设备和基于位置的服务(LBS)的普及引起了人们对其用户位置隐私的极大关注。保护位置隐私的一种流行方法是使LBS系统的用户匿名。在本文中,我们介绍了一种关于位置隐私的信息理论概念,我们称之为完美位置隐私。然后,我们演示LBS系统应如何使用匿名来实现定义的完美位置隐私。我们根据用户移动的两种模型研究完美的位置隐私。首先,我们假设用户的当前位置与其过去的位置无关。使用此独立的均匀分布(i.i.d.)模型,我们表明,如果在对手进行O(n2 / r-1)观察之前对该用户的笔名进行了更改,则该用户具有完美的位置隐私。在此,n是网络中的用户数,r是所有可能位置的数。接下来,我们使用马尔可夫链对用户的运动进行建模,以更好地对现实世界的运动模式进行建模。我们表明,如果在用户的对手收集O(n 2 / IEI-r观测值之前更改了用户的笔名,则该用户可以实现完美的位置隐私,其中IEI是用户的马尔可夫链模型中的边数。

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